From: the.beez.speaks@gmail.com   
      
   I used something similar - but with a whole slew of stack operations.   
   Very handy thingy. I use it until this day.   
      
   ( abc -- abcabc)   >r over over r@ rot rot r> \ >r 2dup r@ -rot r>   
      
   Hans Bezemer   
      
   On 30-09-2025 18:33, Anton Ertl wrote:   
   > I wanted to generate a random sequence consisting of a number, NOOP,   
   > and DROP.  When EVALUATEing the sequence, starting with an empty   
   > stack, it should end with an empty stack, and should not underflow the   
   > stack.   
   >   
   > I implemented this twice.  The first attempt just generated a random   
   > word/number in the normal case, and a specific kind of word/number in   
   > the boundary cases:   
   >   
   > : genseq {: u -- :}   
   >      0 u 0 do   
   >          case   
   >              dup 0= ?of 1+ ." 9 " endof   
   >              dup i + u u>= ?of 1- ." drop " endof   
   >              dup i + 1+ u u>= ?of ." noop " endof   
   >              rnd 3 um* nip 1- dup case   
   >                  -1 of ." drop " endof   
   >                  0  of ." noop " endof   
   >                  1  of ." 8 " endof   
   >              endcase   
   >              +   
   >              0 endcase   
   >      loop   
   >      drop ;   
   >   
   > When I do 16 GENSEQ with seed 1234, I get the following sequence:   
   >   
   > 9 drop 9 8 8 noop drop drop 8 noop drop noop noop 8 drop drop   
   >   
   > The requirements are distributed across several places in this word,   
   > which I did not like.  I also did not like the non-randomness of the   
   > sequence of DROPs at the end, and the non-randomness of the 9 whenever   
   > the stack is empty.  I also found that I needed to add a clause for   
   > when the stack depth is one less than the number of remaining words.   
   >   
   > So I thought about other ways to do it.   
   >   
   > Eventually I came up with the following approach: Starts with counters   
   > for the different kinds of words/numbers.  Whenever one word/number is   
   > generated, its counter is reduced.  At each step the probability of   
   > generating a kind of word/number is proportional to the remaining   
   > counter for that word/number.  The same-depth requirement is   
   > implemented by having the same initial counter for the number and   
   > DROP.  The no-underflow requirement is implemented by skipping the   
   > output of a DROP if the count of remaining DROPs = the count of the   
   > remaining numbers.   
   >   
   > Here's the code:   
   >   
   > create counts 3 cells allot   
   >   
   > : initcounts ( u -- )   
   >      dup 3 / dup counts ! dup counts 2 th ! 2* - counts cell+ ! ;   
   >   
   > : .counts ( -- )   
   >      counts 3 cell array>mem mem+do   
   >          i @ 4 .r   
   >      loop ;   
   >   
   > : countsth-- ( u -- )   
   >      -1 counts rot th +! ;   
   >   
   > : select1 ( u -- )   
   >      \ u is the index of the word   
   >      dup case   
   >          0 of ." 9 "    countsth-- endof   
   >          1 of ." noop " countsth-- endof   
   >          2 of counts @ counts 2 th @ u< if   
   >                  ." drop " countsth--   
   >              else   
   >                  drop endif   
   >          endof   
   >      endcase ;   
   >   
   > : sum ( addr u -- u2 )   
   >      \ addr u is an array with u elements, u2 is the sum of the elements   
   >      0 -rot cell array>mem mem+do   
   >          i @ +   
   >      loop ;   
   >   
   > : genseq ( u -- )   
   >      initcounts   
   >      begin   
   >          counts 3 sum dup while   
   >              rnd um* nip ( sum )   
   >              3 0 u+do ( sum1 )   
   >                  counts i th @ 2dup u< if   
   >                      i select1 then   
   >                  - loop   
   >              drop   
   >      repeat   
   >      drop ;   
   >   
   > The code is much longer, but I like it better.  The requirements are   
   > concentrated in two places.   
   >   
   > 16 GENSEQ generates   
   >   
   > 9 9 noop noop drop noop 9 drop noop drop noop 9 drop 9 noop drop   
   >   
   > for seed 123.  A disadvantage of this approach is that it does not   
   > generate a word/number on each iteration through the main loop.  I   
   > have thought about how to achieve this, but the result would be quite   
   > a bit more complex; it's also only a minor issue.  E.g., for   
   > generating 1000 words/numbers with seed 123, the main loop has 1036   
   > iterations.   
   >   
   > The second approach takes quite a bit more time; for generating a   
   > million words/numbers into a string on a Zen 4, 192_876_892 cycles   
   > compared to 146_644_156 cycles.   
   >   
   > The original goal was to produce a sequence where various parts of the   
   > text interpreter have branch mispredictions; the less predictable the   
   > sequence, the better.  In this respect the second sequence is   
   > significantly better.  For a sequence of 1000 words/numbers,   
   > text-interpreted 1000 times, the number of mispredictions is:   
   >   
   > 728_322 first approach   
   > 821_813 second approach   
   >   
   > (with 247_125 mispredictions coming from (mainly) Gforth startup).   
   >   
   > - anton   
      
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